Inference made about association and causation primarily depends upon the application of epidemiological data to rigorous statistical analyses of data on putative factors that are linked with the outcome variable. This module builds upon applying concepts of biostatistics and interpreting the associations of an outcome variable with several independent variables to assess the strength and direction of association. Students are taught about developing regression models based conceptually on type of outcome measure, the scale of outcome measurement, study design, sequence of exposure to risk and occurrence of outcome, and the sample design. They also learn to identify variables for inclusion in the model based on conceptual models, steps of inclusion in the model, aimed at identifying collinearity, effects modifiers, confounding factors, and appreciate the pitfalls of various regressions methods and ways to overcome them in regression models.
Inference made about association and causation primarily depends upon the application of epidemiological data to rigorous statistical analyses of data on putative factors that are linked with the outcome variable. This module builds upon applying concepts of biostatistics and interpreting the associations of an outcome variable with several independent variables to assess the strength and direction of association. Students are taught about developing regression models based conceptually on type of outcome measure, the scale of outcome measurement, study design, sequence of exposure to risk and occurrence of outcome, and the sample design. They also learn to identify variables for inclusion in the model based on conceptual models, steps of inclusion in the model, aimed at identifying collinearity, effects modifiers, confounding factors, and appreciate the pitfalls of various regressions methods and ways to overcome them in regression models.
- Instructor: CHANDRASHEKHAR THUMMALA HALLY SREERAMA REDDY
Skill Level: Beginner